Nat Chem Biol. 2024 Jul 29. doi: 10.1038/s41589-024-01668-4. Online ahead of print.

ABSTRACT

Molecular glues are proximity-inducing small molecules that have emerged as an attractive therapeutic approach. However, developing molecular glues remains challenging, requiring innovative mechanistic strategies to stabilize neoprotein interfaces and expedite discovery. Here we unveil a trans-labeling covalent molecular glue mechanism, termed 'template-assisted covalent modification'. We identified a new series of BRD4 molecular glue degraders that recruit CUL4DCAF16 ligase to the second bromodomain of BRD4 (BRD4BD2). Through comprehensive biochemical, structural and mutagenesis analyses, we elucidated how pre-existing structural complementarity between DCAF16 and BRD4BD2 serves as a template to optimally orient the degrader for covalent modification of DCAF16Cys58. This process stabilizes the formation of BRD4-degrader-DCAF16 ternary complex and facilitates BRD4 degradation. Supporting generalizability, we found that a subset of degraders also induces GAK-BRD4BD2 interaction through trans-labeling of GAK. Together, our work establishes 'template-assisted covalent modification' as a mechanism for covalent molecular glues, which opens a new path to proximity-driven pharmacology.

PMID:39075252 | DOI:10.1038/s41589-024-01668-4

Sci Rep. 2024 Jul 29;14(1):17357. doi: 10.1038/s41598-024-68264-3.

ABSTRACT

The environmental contamination by extremophile Aspergillus species, i.e., Aflatoxin B1, is hardly controllable in Southeast Asia and Sub-Saharan Africa, which lack handling resources and controlled storage facilities. Acute aflatoxicosis poisoning from aflatoxin-prone dietary staples could cause acute hepatic necrosis, acute liver failure, and death. Here, as the cheaper, more straightforward, and facile on-site diagnostic kit is needed, we report an ultraviolet-excitable optical aptasensor based on a fluorinated ethylene propylene film strip. Molecular dynamics on the aptamer.AFB1 complex revealed that the AFB1 to the aptamer increases the overall structural stability, suggesting that the aptamer design is suitable for the intended application. Under various influencing factors, the proposed label-free strategy offers a fast 20-min on-site fabrication simplicity and 19-day shelf-life. The one-pot incubation provides an alternative to catalytic detection and exhibited 4 times reusability. The recovery of crude brown sugar, processed peanuts, and long-grain rice were 102.74 ± 0.41 (n = 3), 86.90 ± 3.38 (n = 3), and 98.50 ± 0.42 (n = 3), comparable to High-Performance Liquid Chromatography-Photodiode Array Detector results. This study is novel owing to the peculiar UV-active spectrum fingerprint and the convenient use of hydrophobic film strips that could promote breakthrough innovations and new frontiers for on-site/forensic detection of environmental pollutants.

PMID:39075202 | DOI:10.1038/s41598-024-68264-3

Nat Biotechnol. 2024 Jul 29. doi: 10.1038/s41587-024-02316-x. Online ahead of print.

ABSTRACT

Mass cytometry uses metal-isotope-tagged antibodies to label targets of interest, which enables simultaneous measurements of ~50 proteins or protein modifications in millions of single cells, but its sensitivity is limited. Here, we present a signal amplification technology, termed Amplification by Cyclic Extension (ACE), implementing thermal-cycling-based DNA in situ concatenation in combination with 3-cyanovinylcarbazole phosphoramidite-based DNA crosslinking to enable signal amplification simultaneously on >30 protein epitopes. We demonstrate the utility of ACE in low-abundance protein quantification with suspension mass cytometry to characterize molecular reprogramming during the epithelial-to-mesenchymal transition as well as the mesenchymal-to-epithelial transition. We show the capability of ACE to quantify the dynamics of signaling network responses in human T lymphocytes. We further present the application of ACE in imaging mass cytometry-based multiparametric tissue imaging to identify tissue compartments and profile spatial aspects related to pathological states in polycystic kidney tissues.

PMID:39075149 | DOI:10.1038/s41587-024-02316-x

PLoS Pathog. 2024 Jul 29;20(7):e1012236. doi: 10.1371/journal.ppat.1012236. Online ahead of print.

ABSTRACT

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

PMID:39074163 | DOI:10.1371/journal.ppat.1012236

Phys Rev Lett. 2024 Jul 12;133(2):028402. doi: 10.1103/PhysRevLett.133.028402.

ABSTRACT

A fundamental question about biomolecular condensates is how distinct condensates can emerge from the interplay of different components. Here we present a minimal model of droplet differentiation where phase separated droplets demix into two types with different chemical modifications triggered by enzymatic reactions. We use numerical solutions to Cahn-Hilliard equations with chemical reactions and an effective droplet model to reveal the switchlike behavior. Our work shows how condensate identities in cells could result from competing enzymatic actions.

PMID:39073969 | DOI:10.1103/PhysRevLett.133.028402

Bioinformatics. 2024 Jul 29:btae480. doi: 10.1093/bioinformatics/btae480. Online ahead of print.

ABSTRACT

MOTIVATION: Unsupervised clustering of single-cell RNA sequencing (scRNA-seq) data holds the promise of characterizing known and novel cell type in various biological and clinical contexts. However, intrinsic multi-scale clustering resolutions poses challenges to deal with multiple sources of variability in the high-dimensional and noisy data.

RESULTS: We present ClusterMatch, a stable match optimization model to align scRNA-seq data at the cluster level. In one hand, ClusterMatch leverages the mutual correspondence by canonical correlation analysis (CCA) and multi-scale Louvain clustering algorithms to identify cluster with optimized resolutions. In the other hand it utilizes stable matching framework to align scRNA-seq data in the latent space while maintaining interpretability with overlapped marker gene set. Through extensive experiments, we demonstrate the efficacy of ClusterMatch in data integration, cell type annotation, and cross-species/timepoint alignment scenarios. Our results show ClusterMatch's ability to utilize both global and local information of scRNA-seq data, sets the appropriate resolution of multi-scale clustering, and offers interpretability by utilizing marker genes.

AVAILABILITY: The code of CusterMatch software is freely available at https://github.com/AMSSwanglab/ClusterMatch.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:39073888 | DOI:10.1093/bioinformatics/btae480

J Chem Theory Comput. 2024 Jul 29. doi: 10.1021/acs.jctc.4c00435. Online ahead of print.

ABSTRACT

In molecular dynamics simulations, rare events, such as protein folding, are typically studied using enhanced sampling techniques, most of which are based on the definition of a collective variable (CV) along which acceleration occurs. Obtaining an expressive CV is crucial, but often hindered by the lack of information about the particular event, e.g., the transition from unfolded to folded conformation. We propose a simulation-free data augmentation strategy using physics-inspired metrics to generate geodesic interpolations resembling protein folding transitions, thereby improving sampling efficiency without true transition state samples. This new data can be used to improve the accuracy of classifier-based methods. Alternatively, a regression-based learning scheme for CV models can be adopted by leveraging the interpolation progress parameter.

PMID:39073442 | DOI:10.1021/acs.jctc.4c00435

Acta Physiol (Oxf). 2024 Jul 29:e14209. doi: 10.1111/apha.14209. Online ahead of print.

ABSTRACT

AIM: Mitochondrial uncoupling protein 1 (UCP1) is a unique protein of brown adipose tissue. Upon activation by free fatty acids, UCP1 facilitates a thermogenic net proton flux across the mitochondrial inner membrane. Non-complexed purine nucleotides inhibit this fatty acid-induced activity of UCP1. The most available data have been generated from rodent model systems. In light of its role as a putative pharmacological target for treating metabolic disease, in-depth analyses of human UCP1 activity, regulation, and structural features are essential.

METHODS: In the present study, we established a doxycycline-regulated cell model with inducible human or murine UCP1 expression and conducted functional studies using respirometry comparing wild-type and mutant variants of human UCP1.

RESULTS: We demonstrate that human and mouse UCP1 exhibit similar specific fatty acid-induced activity but a different inhibitory potential of purine nucleotides. Mutagenesis of non-conserved residues in human UCP1 revealed structural components in α-helix 56 and α-helix 6 crucial for uncoupling function.

CONCLUSION: Comparative studies of human UCP1 with other orthologs can provide new insights into the structure-function relationship for this mitochondrial carrier and will be instrumental in searching for new activators.

PMID:39072954 | DOI:10.1111/apha.14209

Adv Sci (Weinh). 2024 Jul 29:e2310304. doi: 10.1002/advs.202310304. Online ahead of print.

ABSTRACT

Despite the success of immunotherapy in treating hepatocellular carcinoma (HCC), HCC remains a severe threat to health. Here, a crucial transcription factor, SOX12, is revealed that induces the immunosuppression of liver tumor microenvironment. Overexpressing SOX12 in HCC syngeneic models increases intratumoral regulatory T-cell (Treg) infiltration, decreases CD8+T-cell infiltration, and hastens HCC metastasis. Hepatocyte-specific SOX12 knockout attenuates DEN/CCl4-induced HCC progression and metastasis, whereas hepatocyte-specific SOX12 knock-in accelerates these effects. Mechanistically, SOX12 transcriptionally activates C-C motif chemokine ligand 22 (CCL22) expression to promote the recruitment and suppressive activity of Tregs. Moreover, SOX12 transcriptionally upregulates CD274 expression to suppress CD8+T-cell infiltration. Either knockdown of CCL22 or PD-L1 dampens SOX12-mediated HCC metastasis. Blocking of CC chemokine receptor 4 (CCR4), a receptor for CCL22, by inhibitor C-021 or Treg-specific knockout of CCR4 inhibits SOX12-mediated HCC metastasis. Transforming growth factor-β1 (TGF-β1)/TGFβR1-Smad2/3/4 is identified as a key upstream signaling for SOX12 overexpression in HCC cells. Combining C-021 or TGFβR1 inhibitor galunisertib with anti-PD-L1 exhibits an enhanced antitumor effect in two HCC models. Collectively, the findings demonstrate that SOX12 contributes to HCC immunosuppression through the CCL22/CCR4-Treg and PD-L1-CD8+T axes. Blocking of CCR4 or TGFβR1 improves the efficacy of anti-PD-L1 in SOX12-mediated HCC.

PMID:39072947 | DOI:10.1002/advs.202310304

Eur J Neurosci. 2024 Jul 28. doi: 10.1111/ejn.16465. Online ahead of print.

ABSTRACT

Electroencephalogram (EEG) and electromyogram (EMG) are fundamental tools in sleep research. However, investigations into the statistical properties of rodent EEG/EMG signals in the sleep-wake cycle have been limited. The lack of standard criteria in defining sleep stages forces researchers to rely on human expertise to inspect EEG/EMG. The recent increasing demand for analysing large-scale and long-term data has been overwhelming the capabilities of human experts. In this study, we explored the statistical features of EEG signals in the sleep-wake cycle. We found that the normalized EEG power density profile changes its lower and higher frequency powers to a comparable degree in the opposite direction, pivoting around 20-30 Hz between the NREM sleep and the active brain state. We also found that REM sleep has a normalized EEG power density profile that overlaps with wakefulness and a characteristic reduction in the EMG signal. Based on these observations, we proposed three simple statistical features that could span a 3D space. Each sleep-wake stage formed a separate cluster close to a normal distribution in the 3D space. Notably, the suggested features are a natural extension of the conventional definition, making it useful for experts to intuitively interpret the EEG/EMG signal alterations caused by genetic mutations or experimental treatments. In addition, we developed an unsupervised automatic staging algorithm based on these features. The developed algorithm is a valuable tool for expediting the quantitative evaluation of EEG/EMG signals so that researchers can utilize the recent high-throughput genetic or pharmacological methods for sleep research.

PMID:39072800 | DOI:10.1111/ejn.16465

Trends Analyt Chem. 2024 Sep;178:117852. doi: 10.1016/j.trac.2024.117852. Epub 2024 Jul 3.

ABSTRACT

Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics generates large datasets comprising hundreds to thousands of metabolites with complex relationships. AI, aiming to mimic human intelligence through computational modeling, possesses extraordinary capabilities for big data analysis. In this review, we provide a recent overview of the methodologies and applications of AI in metabolomics studies in the context of systems biology and human health. We first introduce the AI concept, history, and key algorithms for machine learning and deep learning, summarizing their strengths and weaknesses. We then discuss studies that have successfully used AI across different aspects of metabolomic analysis, including analytical detection, data preprocessing, biomarker discovery, predictive modeling, and multi-omics data integration. Lastly, we discuss the existing challenges and future perspectives in this rapidly evolving field. Despite limitations and challenges, the combination of metabolomics and AI holds great promises for revolutionary advancements in enhancing human health.

PMID:39071116 | PMC:PMC11271759 | DOI:10.1016/j.trac.2024.117852

Small Sci. 2023 Dec;3(12):2300095. doi: 10.1002/smsc.202300095. Epub 2023 Nov 8.

ABSTRACT

Yeast surface display (YSD) is a powerful tool in biotechnology that links genotype to phenotype. In this review, the latest advancements in protein engineering and high-throughput screening based on YSD are covered. The focus is on innovative methods for overcoming challenges in YSD in the context of biotherapeutic drug discovery and diagnostics. Topics ranging from titrating avidity in YSD using transcriptional control to the development of serological diagnostic assays relying on serum biopanning and mitigation of unspecific binding are covered. Screening techniques against nontraditional cellular antigens, such as cell lysates, membrane proteins, and extracellular matrices are summarized and techniques are further delved into for expansion of the chemical repertoire, considering protein-small molecule hybrids and noncanonical amino acid incorporation. Additionally, in vivo gene diversification and continuous evolution in yeast is discussed. Collectively, these techniques enhance the diversity and functionality of engineered proteins isolated via YSD, broadening the scope of applications that can be addressed. The review concludes with future perspectives and potential impact of these advancements on protein engineering. The goal is to provide a focused summary of recent progress in the field.

PMID:39071103 | PMC:PMC11271970 | DOI:10.1002/smsc.202300095

ACS Cent Sci. 2024 Jun 21;10(7):1371-1382. doi: 10.1021/acscentsci.4c00354. eCollection 2024 Jul 24.

ABSTRACT

Radiotherapy is commonly used to treat cancer, and localized energy deposited by radiotherapy has the potential to chemically uncage prodrugs; however, it has been challenging to demonstrate prodrug activation that is both sustained in vivo and truly localized to tumors without affecting off-target tissues. To address this, we developed a series of novel phenyl-azide-caged, radiation-activated chemotherapy drug-conjugates alongside a computational framework for understanding corresponding pharmacokinetic and pharmacodynamic (PK/PD) behaviors. We especially focused on an albumin-bound prodrug of monomethyl auristatin E (MMAE) and found it blocked tumor growth in mice, delivered a 130-fold greater amount of activated drug to irradiated tumor versus unirradiated tissue, was 7.5-fold more efficient than a non albumin-bound prodrug, and showed no appreciable toxicity compared to free or cathepsin-activatable drugs. These data guided computational modeling of drug action, which indicated that extended pharmacokinetics can improve localized and cumulative drug activation, especially for payloads with low vascular permeability and diffusivity and particularly in patients receiving daily treatments of conventional radiotherapy for weeks. This work thus offers a quantitative PK/PD framework and proof-of-principle experimental demonstration of how extending prodrug circulation can improve its localized activity in vivo.

PMID:39071065 | PMC:PMC11273447 | DOI:10.1021/acscentsci.4c00354

MedComm (2020). 2024 Jul 28;5(8):e666. doi: 10.1002/mco2.666. eCollection 2024 Aug.

ABSTRACT

Development of potent and broad-spectrum drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains one of the top priorities, especially in the cases of the emergence of mutant viruses and inability of current vaccines to prevent viral transmission. In this study, we have generated a novel membrane fusion-inhibitory lipopeptide IPB29, which is currently under clinical trials; herein, we report its design strategy and preclinical data. First, we surprisingly found that IPB29 with a rigid linker between the peptide sequence and lipid molecule had greatly improved α-helical structure and antiviral activity. Second, IPB29 potently inhibited a large panel of SARS-CoV-2 variants including the previously and currently circulating viruses, such as Omicron XBB.5.1 and EG.5.1. Third, IPB29 could also cross-neutralize the bat- and pangolin-isolated SARS-CoV-2-related CoVs (RatG13, PCoV-GD, and PCoV-GX) and other human CoVs (SARS-CoV, MERS-CoV, HCoV-NL63, and HCoV-229E). Fourth, IPB29 administrated as an inhalation solution (IPB29-IS) in Syrian hamsters exhibited high therapeutic and preventive efficacies against SARS-CoV-2 Delta or Omicron variant. Fifth, the pharmacokinetic profiles and safety pharmacology of IPB29-IS were extensively characterized, providing data to support its evaluation in humans. In conclusion, our studies have demonstrated a novel design strategy for viral fusion inhibitors and offered an ideal drug candidate against SARS-CoV-2 and other coronaviruses.

PMID:39070180 | PMC:PMC11283584 | DOI:10.1002/mco2.666

IUCrJ. 2024 Sep 1. doi: 10.1107/S2052252524005918. Online ahead of print.

ABSTRACT

Cryogenic electron microscopy (cryo-EM) is a pivotal technique for imaging macromolecular structures. However, despite extensive processing of large image sets collected in cryo-EM experiments to amplify the signal-to-noise ratio, the reconstructed 3D protein-density maps are often limited in quality due to residual noise, which in turn affects the accuracy of the macromolecular representation. Here, crefDenoiser is introduced, a denoising neural network model designed to enhance the signal in 3D cryo-EM maps produced with standard processing pipelines. The crefDenoiser model is trained without the need for `clean' ground-truth target maps. Instead, a custom dataset is employed, composed of real noisy protein half-maps sourced from the Electron Microscopy Data Bank repository. Competing with the current state-of-the-art, crefDenoiser is designed to optimize for the theoretical noise-free map during self-supervised training. We demonstrate that our model successfully amplifies the signal across a wide variety of protein maps, outperforming a classic map denoiser and following a network-based sharpening model. Without biasing the map, the proposed denoising method leads to improved visibility of protein structural features, including protein domains, secondary structure elements and modest high-resolution feature restoration.

PMID:39069881 | DOI:10.1107/S2052252524005918

Int J Sports Physiol Perform. 2024 Jul 27:1-6. doi: 10.1123/ijspp.2023-0287. Online ahead of print.

ABSTRACT

PURPOSE: To assess the effect of 2 work-matched efforts of different intensities on subsequent performance in well-trained cyclists.

METHODS: The present study followed a randomized controlled crossover design. Twelve competitive junior cyclists volunteered to participate (age, 17 [1] y; maximum oxygen uptake, 71.0 [4.7] mL·kg-1·min-1). The power-duration relationship was assessed through 2-minute, 5-minute, and 12-minute field tests under fresh conditions (control). On subsequent days and following a randomized order, participants repeated the aforementioned tests after 2 training sessions matched for mechanical work (∼15 kJ/kg) of different intensities (ie, a moderate-intensity continuous-training [60%-70% of critical power; CP] session or a session including high-intensity intervals [3-min repetition bouts at 110%-120% of the CP interspersed by 3-min rest periods]).

RESULTS: A significantly lower power output was found in the 2-minute test after the high-intensity training session compared not only with the control condition (-8%, P < .001) but also with the moderate-intensity continuous-training session (-7%, P = .003), with no significant differences between the latter conditions. No significant differences between conditions were found for the remaining tests. As a consequence, the high-intensity training session resulted in significantly lower W' values compared to both the control condition (-27%, P = .001) and the moderate-intensity continuous-training session (-26%, P = .012), with no differences between the 2 latter conditions and with no differences for CP.

CONCLUSION: A session including high-intensity intermittent efforts induces a greater fatigue, particularly in short-duration efforts and W', than a work-matched continuous-training session of moderate intensity.

PMID:39069285 | DOI:10.1123/ijspp.2023-0287

Int J Sports Med. 2024 Jul 28. doi: 10.1055/a-2348-0238. Online ahead of print.

ABSTRACT

This study aimed to compare the acute inflammatory response following high-intensity eccentric exercise between resistance-trained young and master athletes with similar performance levels. Resistance-trained young (n=8; 22±2 years) and master (n=8; 52±4 years) male athletes of a similar performance level performed a standardized high-intensity eccentric squat exercise protocol (10 sets of half-squats at 70% of 1-repetition maximum). The serum concentration of 20 biomarkers related to tissue damage, inflammation, remodeling, and repair was measured at baseline, immediately after exercise, and over a 72 h recovery period. Both groups experienced similar muscle damage as evidenced by a comparable increase in creatine kinase activity 24 h after exercise (p<0.001). Interleukin-6 (p=0.009) and growth hormone (p<0.001) increased immediately post-exercise in both groups. Monocyte chemoattractant protein-1 increased immediately post-exercise only in young athletes (p=0.003) and then decreased 24 h later. There were no significant differences for the remaining variables, including cell markers related to neutrophil/macrophage activation or pro/anti-inflammatory cytokines. Resistance-trained young and master athletes, matched for performance level, showed an overall similar inflammatory response to eccentric exercise, possibly reflecting regulatory mechanisms or immunological adaptations to chronic stimulation in master athletes.

PMID:39068934 | DOI:10.1055/a-2348-0238

Cell Rep. 2024 Jul 26;43(8):114552. doi: 10.1016/j.celrep.2024.114552. Online ahead of print.

ABSTRACT

The non-essential amino acid serine is a critical nutrient for cancer cells due to its diverse biosynthetic functions. While some tumors can synthesize serine de novo, others are auxotrophic and therefore reliant on serine uptake. Importantly, despite several transporters being known to be capable of transporting serine, the transporters that mediate serine uptake in cancer cells are not known. Here, we characterize the amino acid transporter ASCT2 (SLC1A5) as a major contributor to serine uptake in cancer cells. ASCT2 is well known as a glutamine transporter in cancer, and our work demonstrates that serine and glutamine compete for uptake through ASCT2. We further show that ASCT2-mediated serine uptake is essential for purine nucleotide biosynthesis and that estrogen receptor α (ERα) promotes serine uptake by directly activating SLC1A5 transcription. Collectively, our work defines an additional important role for ASCT2 as a serine transporter in cancer and evaluates ASCT2 as a potential therapeutic target.

PMID:39068660 | DOI:10.1016/j.celrep.2024.114552

STAR Protoc. 2024 Jul 26;5(3):103211. doi: 10.1016/j.xpro.2024.103211. Online ahead of print.

ABSTRACT

When plants are subjected to drought, it is impossible to obtain xylem sap for subsequent biochemical and molecular analysis using root pressure exudate, the conventional approach. Here, we present a protocol for collecting xylem sap from drought-treated tomato plants using a pressure chamber. We describe steps for how to prepare plants, apply drought, and use the pressure chamber to collect the xylem sap. Using this technique, one can obtain 500-700 μL of xylem sap in just 5-7 min. For complete details on the use and execution of this protocol, please refer to Alexou and Peuke.1.

PMID:39068658 | DOI:10.1016/j.xpro.2024.103211

STAR Protoc. 2024 Jul 27;5(3):103220. doi: 10.1016/j.xpro.2024.103220. Online ahead of print.

ABSTRACT

AS1411-NCL-MDM2-based proteolysis-targeting chimeras (ANM-PROTACs) are capable of inducing selective degradation of transcription factors (TFs) in tumor cells. Here, we present a protocol for constructing ANM-PROTACs. We describe steps for molecular design of the ANM-PROTACs, assembly and characterization of the ANM-PROTACs, and initial assessment of in vitro TF degradation potency. We then detail procedures for validation of selective degradation of TFs via proteomic analysis. This protocol has been successfully applied to degrade various TFs across multiple tumor cell lines. For complete details on the use and execution of this protocol, please refer to Fu et al.1.

PMID:39068654 | DOI:10.1016/j.xpro.2024.103220